# ---------------------------------------------
@STRING{SIGGRAPHASIA = "SIGGRAPH ASIA"}
@STRING{SIGGRAPH = "SIGGRAPH"}
@STRING{AISTATS = "AISTATS"}
@STRING{SIGKDD = "SIGKDD"}
@STRING{ICASSP = "ICASSP"}
@STRING{ACMTOG = "ACM Transactions on Graphics"}
@STRING{NIPSw = "NeurIPS Workshop"}
@STRING{ICMLw = "ICML Workshop"}
@STRING{ACMMM = "ACM MM"}
@STRING{IJCAI = "IJCAI"}
@STRING{IJCNN = "IJCNN"}
@STRING{SYSML = "SysML"}
@STRING{PAMI = "PAMI"}
@STRING{IJCV = "IJCV"}
@STRING{JMLR = "JMLR"}
@STRING{CVIU = "CVIU"}
@STRING{NIPS = "NeurIPS"}
@STRING{ICLR = "ICLR"}
@STRING{CVPR = "CVPR"}
@STRING{ECCV = "ECCV"}
@STRING{ICCV = "ICCV"}
@STRING{ICML = "ICML"}
@STRING{AAAI = "AAAI"}
@STRING{ICIP = "ICIP"}
@STRING{BMVC = "BMVC"}
@STRING{ICPR = "ICPR"}
@STRING{ICME = "ICME"}
@STRING{NPAR = "NPAR"}
@STRING{WACV = "WACV"}
@STRING{OSDI = "IEEE Symposium on Operating Systems Design and Implementation"}
@STRING{TIP = "TIP"}
@STRING{TIT = "TIT"}
@STRING{VMV = "VMV"}
@STRING{PR = "PR"}
# ---------------------------------------------

@inproceedings{wei-2001-texture,
  title={Texture synthesis over arbitrary manifold surfaces},
  author={Wei, Li-Yi and Levoy, Marc},
  booktitle=SIGGRAPH,
  year={2001}
}

@article{julesz-1962visual,
  title={Visual pattern discrimination},
  author={Julesz, Bela},
  journal={IRE transactions on Information Theory},
  volume={8},
  number={2},
  pages={84--92},
  year={1962}
}

@inproceedings{Wetbrush-SiggraphAsia-2015,
  title={Wetbrush: GPU-based 3D painting simulation at the bristle level},
  author={Chen, Zhili and Kim, Byungmoon and Ito, Daichi and Wang, Huamin},
  booktitle=SIGGRAPHASIA,
  year={2015}
}

@inproceedings{kwatra-2003-graphcut,
  title={Graphcut textures: image and video synthesis using graph cuts},
  author={Kwatra, Vivek and Sch{\"o}dl, Arno and Essa, Irfan and Turk, Greg and Bobick, Aaron},
  booktitle=SIGGRAPH,
  OPTvolume={22},
  OPTnumber={3},
  OPTpages={277--286},
  year={2003}
}

@inproceedings{heeger-1995-pyramid,
  title={Pyramid-based texture analysis/synthesis},
  author={Heeger, David J and Bergen, James R},
  booktitle=SIGGRAPH,
  year={1995}
}

@inproceedings{de-1997-multiresolution,
  title={Multiresolution sampling procedure for analysis and synthesis of texture images},
  author={De Bonet, Jeremy S},
  booktitle=SIGGRAPH,
  year={1997}
}

@article{portilla-2000-parametric,
  title={A parametric texture model based on joint statistics of complex wavelet coefficients},
  author={Portilla, Javier and Simoncelli, Eero P},
  journal=IJCV,
  volume={40},
  number={1},
  pages={49--70},
  year={2000}
}

@inproceedings{simoncelli-1995-steerable,
  title={The steerable pyramid: a flexible architecture for multi-scale derivative computation.},
  author={Simoncelli, Eero P and Freeman, William T},
  booktitle=ICIP,
  year={1995}
}

@inproceedings{Perceptual-ECCV2016,
  title={Perceptual losses for real-time style transfer and super-resolution},
  author={Johnson, Justin and Alahi, Alexandre and Fei-Fei, Li},
  booktitle=ECCV,
  year={2016}
}

@inproceedings{Texturenet-ICML2016,
  title={Texture Networks: Feed-forward Synthesis of Textures and Stylized Images},
  author={Ulyanov, Dmitry and Lebedev, Vadim and Vedaldi, Andrea and Lempitsky, Victor},
  booktitle=ICML,
  year={2016}
}

@inproceedings{GatysTexture-NIPS2015,
  title={Texture synthesis using convolutional neural networks},
  author={Gatys, Leon A and Ecker, Alexander S and Bethge, Matthias},
  booktitle=NIPS,
  year={2015}
}

@inproceedings{GatysTransfer-CVPR2016,
  title={Image style transfer using convolutional neural networks},
  author={Gatys, Leon A and Ecker, Alexander S and Bethge, Matthias},
  booktitle=CVPR,
  year={2016}
}

@inproceedings{MrfTransfer-CVPR2016,
  title={Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis},
  author={Li, Chuan and Wand, Michael},
  booktitle=CVPR,
  year={2016}
}

@inproceedings{Frigo-2016-CVPR,
 author = {Frigo, Oriel and Sabater, Neus and Delon, Julie and Hellier, Pierre},
 title = {Split and Match: Example-Based Adaptive Patch Sampling for Unsupervised Style Transfer},
 booktitle = CVPR,
 year = {2016}
}

@inproceedings{MGAN-ECCV2016,
  title={Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks},
  author={Li, Chuan and Wand, Michael},
  booktitle=ECCV,
  year={2016}
}

@inproceedings{Efros1-ICCV1999,
  title={Texture synthesis by non-parametric sampling},
  author={Efros, Alexei A and Leung, Thomas K},
  booktitle=ICCV,
  year={1999}
}

@inproceedings{Efros2-SIGGRAPH2001,
  title={Image quilting for texture synthesis and transfer},
  author={Efros, Alexei A and Freeman, William T},
  booktitle=SIGGRAPH,
  year={2001}
}

@inproceedings{Diversity-NIPS2016,
  title={Improved Techniques for Training {GAN}s},
  author={Salimans, Tim and Goodfellow, Ian and Zaremba, Wojciech and Cheung, Vicki and Radford, Alec and Chen, Xi},
  booktitle=NIPS,
  year={2016}
}

@inproceedings{DTDtexture-CVPR2016,
  title={Describing Textures in the Wild},
  author={M. Cimpoi and S. Maji and I. Kokkinos and S. Mohamed and and A. Vedaldi},
  booktitle=CVPR,
  year={2014}
}

@inproceedings{Wikipainting-BMVC2014,
  title={Recognizing Image Style},
  author={Karayev, Sergey and Trentacoste, Matthew and Han, Helen and Agarwala, Aseem and Darrell, Trevor and Hertzmann, Aaron and Winnemoeller, Holger},
  booktitle=BMVC,
  year={2014}
}

@article{InstanceBN-arxiv-2016,
  title={Instance Normalization: The Missing Ingredient for Fast Stylization},
  author={Ulyanov, Dmitry and  Vedaldi, Andrea and Lempitsky, Victor},
  journal={arXiv preprint arXiv:1607.08022},
  year={2016}
}

@article{Gatys-PreservingColor-2016,
  title={Preserving Color in Neural Artistic Style Transfer},
  author={Gatys, Leon A and Bethge, Matthias and Hertzmann, Aaron  and Shechtman, Eli},
  journal={arXiv preprint arXiv:1606.05897},
  year={2016}
}

@inproceedings{Santiago2018Diverse,
  title={Diverse feature visualizations reveal invariances in early layers of deep neural networks},
  author={Santiago A. Cadena and Marissa A. Weis and Leon A. Gatys and Bethge, Matthias and Alexander S. Ecker},
  booktitle=ECCV,
  year={2018},
}

@inproceedings{GoogleMultiTexture-2016,
  title={A Learned Representation For Artistic Style},
  author={Dumoulin, Vincent and Shlens, Jonathon and Kudlur, Manjunath},
  booktitle=ICLR,
  year={2017}
}

@inproceedings{Doso-CVPR2016-Inverting,
  title={Inverting visual representations with convolutional networks},
  author={Dosovitskiy, Alexey and Brox, Thomas},
  booktitle=CVPR,
  year={2016}
}

@inproceedings{Doso-NIPS2016-Generation,
  title={Generating Images with Perceptual Similarity Metrics based on Deep Networks},
  author={Dosovitskiy, Alexey and Brox, Thomas},
  booktitle=NIPS,
  year={2016}
}

@inproceedings{mahendran-CVPR2015-Inverting,
  title={Understanding deep image representations by inverting them},
  author={Mahendran, Aravindh and Vedaldi, Andrea},
  booktitle=CVPR,
  year={2015}
}

@inproceedings{radford-2015-dcGAN,
  title={Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks},
  author={Radford, Alec and Metz, Luke and Chintala, Soumith},
  booktitle=ICLR,
  year={2016}
}

@inproceedings{goodfellow-2014-GAN,
  title={Generative adversarial nets},
  author={Goodfellow, Ian and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
  booktitle=NIPS,
  year={2014}
}

@inproceedings{denton-2015-LapGAN,
  title={Deep Generative Image Models using a {Laplacian} Pyramid of Adversarial Networks},
  author={Denton, Emily L and Chintala, Soumith and Fergus, Rob and others},
  booktitle=NIPS,
  year={2015}
}

@inproceedings{wei-2000-fast,
  title={Fast texture synthesis using tree-structured vector quantization},
  author={Wei, Li-Yi and Levoy, Marc},
  booktitle=SIGGRAPH,
  year={2000}
}

@inproceedings{Hertz-2001-analogy,
  title={Image analogies},
  author={Hertzmann, Aaron and Jacobs, Charles E and Oliver, Nuria and Curless, Brian and Salesin, David H},
  booktitle=SIGGRAPH,
  year={2001}
}

@article{ashikhmin-2003-fast,
  title={Fast texture transfer},
  author={Ashikhmin, N},
  journal={IEEE Computer Graphics and Applications},
  volume={23},
  number={4},
  pages={38--43},
  year={2003}
}

@inproceedings{lee-2010-directional,
  title={Directional texture transfer},
  author={Lee, Hochang and Seo, Sanghyun and Ryoo, Seungtaek and Yoon, Kyunghyun},
  booktitle=NPAR,
  year={2010}
}

@inproceedings{deng2009imagenet,
  title={Imagenet: A large-scale hierarchical image database},
  author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
  booktitle=CVPR,
  year={2009},
}

@inproceedings{krizhevsky-2012-alexnet,
  title={Imagenet classification with deep convolutional neural networks},
  author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
  booktitle=NIPS,
  year={2012}
}


@inproceedings{szegedy-2015-googlenet,
  title={Going deeper with convolutions},
  author={Szegedy, Christian and Liu, Wei and Jia, Yangqing and Sermanet, Pierre and Reed, Scott and Anguelov, Dragomir and Erhan, Dumitru and Vanhoucke, Vincent and Rabinovich, Andrew},
  booktitle=CVPR,
  year={2015}
}

@inproceedings{dosovitskiy-2015-learning,
  title={Learning to generate chairs with convolutional neural networks},
  author={Dosovitskiy, Alexey and Tobias Springenberg, Jost and Brox, Thomas},
  booktitle=CVPR,
  year={2015}
}

@inproceedings{Gatys2016-control,
  author={Gatys, Leon A and Ecker, Alexander S and Bethge, Matthias and Hertzmann, Aaron and Shechtman, Eli},
  title = {Controlling Perceptual Factors in Neural Style Transfer},
  booktitle=CVPR,
  year={2017}
}

@inproceedings{Texturenet-2017-V2,
  title={Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis},
  author={Ulyanov, Dmitry and Vedaldi, Andrea and Lempitsky, Victor},
  booktitle=CVPR,
  year={2017}
}

@inproceedings{Huang-2017-arbitrary,
  title={Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization},
  author={Huang, Xun and Belongie, Serge},
  booktitle=ICCV,
  year={2017}
}

@article{Zhang-2017-multi,
  title={Multi-style Generative Network for Real-time Transfer},
  author={Zhang, Hang and Dana, Kristin},
  journal={arXiv preprint arXiv:1703.06953},
  year={2017}
}

@article{Wang-2017-zeroshortArbitrary,
  title={ZM-Net: Real-time Zero-shot Image Manipulation Network},
  author={Wang, Hao and Liang, Xiaodan and Zhang, Hao and Yeung, Dit-Yan and Xing, Eric P},
  journal={arXiv preprint arXiv:1703.07255},
  year={2017}
}

@inproceedings{MSRA-2017-stylebank,
  title={Stylebank: An explicit representation for neural image style transfer},
  author={Chen, Dongdong and Yuan, Lu and Liao, Jing and Yu, Nenghai and Hua, Gang},
  booktitle=CVPR,
  year={2017}
}

@article{HistogramLoss-2017,
  title={Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses},
  author={Wilmot, Pierre and Risser, Eric and Barnes, Connelly},
  journal={arXiv preprint arXiv:1701.08893},
  year={2017}
}

@inproceedings{Me-2017-diversified,
  title={Diversified texture synthesis with feed-forward networks},
  author={Li, Yijun and Fang, Chen and Yang, Jimei and Wang, Zhaowen and Lu, Xin and Yang, Ming-Hsuan},
  booktitle=CVPR,
  year={2017}
}

@article{Zhu-2017-cycleGAN,
  title={Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks},
  author={Zhu, Jun-Yan and Park, Taesung and Isola, Phillip and Efros, Alexei A},
  journal={arXiv preprint arXiv:1703.10593},
  year={2017}
}

@article{Chen-2016-swap,
  title={Fast Patch-based Style Transfer of Arbitrary Style},
  author={Chen, Tian Qi and Schmidt, Mark},
  journal={arXiv preprint arXiv:1612.04337},
  year={2016}
}

@inproceedings{Wang-2016-highres,
  title={Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer},
  author={Wang, Xin and Oxholm, Geoffrey and Zhang, Da and Wang, Yuan-Fang},
  booktitle=CVPR,
  year={2017}
}

@inproceedings{Luan-2017-photorealism,
  title={Deep Photo Style Transfer},
  author={Luan, Fujun and Paris, Sylvain and Shechtman, Eli and Bala, Kavita},
  booktitle=CVPR,
  year={2017}
}

@article{WCT-2016,
title={Whitening and Coloring Transforms for Multivariate Gaussian Random Variables},
author={Hossain, Miliha},
journal={Project Rhea},
year={2016}
}

@article{MSRA-2017-visual,
  title={Visual Attribute Transfer through Deep Image Analogy},
  author={Liao, Jing and Yao, Yuan and Yuan, Lu and Hua, Gang and Kang, Sing Bing},
  journal={arXiv preprint arXiv:1705.01088},
  year={2017}
}

@inproceedings{shih2013data,
  title={Data-driven hallucination of different times of day from a single outdoor photo},
  author={Shih, Yichang and Paris, Sylvain and Durand, Fr{\'e}do and Freeman, William T},
  booktitle=SIGGRAPH,
  year={2013}
}

@inproceedings{shih2014style,
  title={Style transfer for headshot portraits},
  author={Shih, YiChang and Paris, Sylvain and Barnes, Connelly and Freeman, William T and Durand, Fr{\'e}do},
  booktitle=SIGGRAPH,
  year={2014}
}

@inproceedings{COCO-lin2014-microsoft,
  title={Microsoft {COCO}: Common objects in context},
  author={Lin, Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
  booktitle=ECCV,
  year={2014}
}

@article{Gonzalez-DIP,
  title={Digital Image Processing (3rd Edition)},
  author={Gonzalez, Rafael C. and Woods, Richard E.},
  journal={Prentice Hall},
  year={2008}
}

@article{Doodle-2016-semantic,
  title={Semantic style transfer and turning two-bit doodles into fine artworks},
  author={Champandard, Alex J},
  journal={arXiv preprint arXiv:1603.01768},
  year={2016}
}

@inproceedings{li2018learning,
  title={Learning Linear Transformations for Fast Arbitrary Style Transfer},
  author={Li, Xueting and Liu, Sifei and Kautz, Jan and Yang, Ming-Hsuan},
  booktitle=CVPR,
  year={2019}
}

@inproceedings{ruder2016artistic,
  title={Artistic style transfer for videos},
  author={Ruder, Manuel and Dosovitskiy, Alexey and Brox, Thomas},
  booktitle={German Conference on Pattern Recognition},
  year={2016},
}

@inproceedings{huang2017real,
  title={Real-time neural style transfer for videos},
  author={Huang, Haozhi and Wang, Hao and Luo, Wenhan and Ma, Lin and Jiang, Wenhao and Zhu, Xiaolong and Li, Zhifeng and Liu, Wei},
  booktitle=CVPR,
  year={2017},
}

@inproceedings{gupta2017characterizing,
  title={Characterizing and improving stability in neural style transfer},
  author={Gupta, Agrim and Johnson, Justin and Alahi, Alexandre and Fei-Fei, Li},
  booktitle=CVPR,
  year={2017}
}

@inproceedings{chen2017coherent,
  title={Coherent online video style transfer},
  author={Chen, Dongdong and Liao, Jing and Yuan, Lu and Yu, Nenghai and Hua, Gang},
  booktitle=ICCV,
  year={2017}
}

@article{jing2017nstreview,
  author= {Yongcheng Jing and Yezhou Yang and Zunlei Feng and Jingwen Ye and Mingli Song},
  title={Neural Style Transfer: {A} Review},
  journal={arXiv preprint arXiv:1705.04058},
  year={2017},
}

@inproceedings{li2017universal,
  title={Universal style transfer via feature transforms},
  author={Li, Yijun and Fang, Chen and Yang, Jimei and Wang, Zhaowen and Lu, Xin and Yang, Ming-Hsuan},
  booktitle=NIPS,
  year={2017}
}

@article{anwar2015structured,
  title={Structured Pruning of Deep Convolutional Neural Networks},
  author={Anwar, Sajid and Hwang, Kyuyeon and Sung, Wonyong},
  journal={arXiv preprint arXiv:1512.08571},
  year={2015}
}

@inproceedings{han2015learning,
  title={Learning both weights and connections for efficient neural network},
  author={Han, Song and Pool, Jeff and Tran, John and Dally, William J},
  booktitle=NIPS,
  year={2015}
}

@inproceedings{han2015deep,
  title={Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding},
  author={Han, Song and Mao, Huizi and Dally, William J},
  booktitle=ICLR,
  year={2016}
}

@inproceedings{hinton2015distilling,
  title={Distilling the knowledge in a neural network},
  author={Hinton, Geoffrey and Vinyals, Oriol and Dean, Jeff},
  journal= NIPSw,
  year={2014}
}

@inproceedings{he2017channel,
  title={Channel pruning for accelerating very deep neural networks},
  author={He, Yihui and Zhang, Xiangyu and Sun, Jian},
  booktitle=ICCV,
  year={2017}
}

@inproceedings{liu2017learning,
  title={Learning efficient convolutional networks through network slimming},
  author={Liu, Zhuang and Li, Jianguo and Shen, Zhiqiang and Huang, Gao and Yan, Shoumeng and Zhang, Changshui},
  booktitle=ICCV,
  year={2017}
}

@inproceedings{he2018soft,
  title={Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks},
  author={He, Yang and Kang, Guoliang and Dong, Xuanyi and Fu, Yanwei and Yang, Yi},
  booktitle=IJCAI,
  year={2018}
}

# FP
@inproceedings{li2017pruning,
  title={Pruning filters for efficient convnets},
  author={Li, Hao and Kadav, Asim and Durdanovic, Igor and Samet, Hanan and Graf, Hans Peter},
  booktitle=ICLR,
  year={2017}
}

# TP
@inproceedings{MolTyrKar17,
  author =   {P. Molchanov and S. Tyree and T. Karras},
  title =     {Pruning Convolutional Neural Networks for Resource Efficient Inference},
  booktitle = ICLR,
  year =      {2017},
}

@article{junginger2018unpaired,
  title={Unpaired High-Resolution and Scalable Style Transfer Using Generative Adversarial Networks},
  author={Junginger, Andrej and Hanselmann, Markus and Strauss, Thilo and Boblest, Sebastian and Buchner, Jens and Ulmer, Holger},
  journal={arXiv preprint arXiv:1810.05724},
  year={2018}
}

@inproceedings{sanakoyeu2018style,
  title={A Style-Aware Content Loss for Real-Time HD Style Transfer},
  author={Sanakoyeu, Artsiom and Kotovenko, Dmytro and Lang, Sabine and Ommer, Bj{\"o}rn},
  booktitle=ECCV,
  year={2018},
}

@inproceedings{romero2014fitnets,
  title={Fitnets: Hints for thin deep nets},
  author={Romero, Adriana and Ballas, Nicolas and Kahou, Samira Ebrahimi and Chassang, Antoine and Gatta, Carlo and Bengio, Yoshua},
  booktitle=ICLR,
  year={2015}
}

@inproceedings{lee2015deeply,
  title={Deeply-supervised nets},
  author={Lee, Chen-Yu and Xie, Saining and Gallagher, Patrick and Zhang, Zhengyou and Tu, Zhuowen},
  booktitle={Artificial Intelligence and Statistics},
  year={2015}
}

@inproceedings{szegedy2016rethinking,
  title={Rethinking the inception architecture for computer vision},
  author={Szegedy, Christian and Vanhoucke, Vincent and Ioffe, Sergey and Shlens, Jon and Wojna, Zbigniew},
  booktitle=CVPR,
  year={2016}
}

@inproceedings{ba2014deep,
  title={Do deep nets really need to be deep?},
  author={Ba, Jimmy and Caruana, Rich},
  booktitle=NIPS,
  year={2014}
}

@book{gooch2001non,
  title={Non-photorealistic rendering},
  author={Gooch, Bruce and Gooch, Amy},
  year={2001},
  publisher={AK Peters/CRC Press}
}

@book{strothotte2002non,
  title={Non-photorealistic computer graphics: modeling, rendering, and animation},
  author={Strothotte, Thomas and Schlechtweg, Stefan},
  year={2002},
  publisher={Morgan Kaufmann}
}

@inproceedings{denton2014exploiting,
  title={Exploiting linear structure within convolutional networks for efficient evaluation},
  author={Denton, Emily L and Zaremba, Wojciech and Bruna, Joan and LeCun, Yann and Fergus, Rob},
  booktitle=NIPS,
  year={2014}
}

@inproceedings{jaderberg2014speeding,
  title={Speeding up convolutional neural networks with low rank expansions},
  author={Jaderberg, Max and Vedaldi, Andrea and Zisserman, Andrew},
  booktitle=BMVC,
  year={2014}
}

@article{lebedev2014speeding,
  title={Speeding-up convolutional neural networks using fine-tuned cp-decomposition},
  author={Lebedev, Vadim and Ganin, Yaroslav and Rakhuba, Maksim and Oseledets, Ivan and Lempitsky, Victor},
  journal={arXiv preprint arXiv:1412.6553},
  year={2014}
}

@inproceedings{zhang2015efficient,
  title={Efficient and accurate approximations of nonlinear convolutional networks},
  author={Zhang, Xiangyu and Zou, Jianhua and Ming, Xiang and He, Kaiming and Sun, Jian},
  booktitle=CVPR,
  year={2015}
}

@ARTICLE{ZhaZouHeSun16,
  author =       {X. Zhang and J. Zou and K. He and J. Sun},
  title =        {Accelerating very deep convolutional networks for classification and detection},
  journal =      PAMI,
  year =         {2016},
  volume =       {38},
  number =       {10},
  pages =        {1943-1955},
}

@inproceedings{liu2015sparse,
  title={Sparse convolutional neural networks},
  author={Liu, Baoyuan and Wang, Min and Foroosh, Hassan and Tappen, Marshall and Pensky, Marianna},
  booktitle=CVPR,
  year={2015}
}

@inproceedings{wen2016learning,
  title={Learning structured sparsity in deep neural networks},
  author={Wen, Wei and Wu, Chunpeng and Wang, Yandan and Chen, Yiran and Li, Hai},
  booktitle=NIPS,
  year={2016}
}

@inproceedings{wang2017structured,
  title={Structured probabilistic pruning for convolutional neural network acceleration},
  author={Wang, Huan and Zhang, Qiming and Wang, Yuehai and Hu, Haoji},
  booktitle=BMVC,
  year={2018}
}

@inproceedings{wang2018structured,
  title={Structured Pruning for Efficient ConvNets via Incremental Regularization},
  author={Wang, Huan and Zhang, Qiming and Wang, Yuehai and Yu, Lu and Hu, Haoji},
  booktitle=IJCNN,
  year={2019}
}

@inproceedings{feng2019triplet,
  title={Triplet Distillation for Deep Face Recognition},
  author={Yushu Feng and Huan Wang and Haoji Hu and Daniel Yi},
  booktitle=ICMLw,
  year={2019}
}

@ARTICLE{CouBen16,
  author =       {M. Courbariaux and Y. Bengio},
  title =        {{BinaryNet}: Training deep neural networks with weights and activations constrained to~$+1$ or~$-1$},
  journal =      {arXiv preprint arXiv:1602.02830},
  year =         {2016},
}

@ARTICLE{LinCouMemBen16,
  author =       {Z. Lin and M. Courbariaux and R. Memisevic and Y. Bengio},
  title =        {Neural networks with few multiplications},
  journal =      {arXiv preprint arXiv:1510.03009},
  year =         {2016},
}

@article{courbariaux2016binarized,
  title={Binarized neural networks: Training deep neural networks with weights and activations constrained to +1 or -1},
  author={Courbariaux, Matthieu and Hubara, Itay and Soudry, Daniel and El-Yaniv, Ran and Bengio, Yoshua},
  journal={arXiv preprint arXiv:1602.02830},
  year={2016}
}

@inproceedings{rastegari2016xnor,
  title={Xnor-net: Imagenet classification using binary convolutional neural networks},
  author={Rastegari, Mohammad and Ordonez, Vicente and Redmon, Joseph and Farhadi, Ali},
  booktitle=ECCV,
  year={2016},
}

@article{zhou2016dorefa,
  title={Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients},
  author={Zhou, Shuchang and Wu, Yuxin and Ni, Zekun and Zhou, Xinyu and Wen, He and Zou, Yuheng},
  journal={arXiv preprint arXiv:1606.06160},
  year={2016}
}

@article{hubara2017quantized,
  title={Quantized neural networks: Training neural networks with low precision weights and activations},
  author={Hubara, Itay and Courbariaux, Matthieu and Soudry, Daniel and El-Yaniv, Ran and Bengio, Yoshua},
  journal=JMLR,
  volume={18},
  number={1},
  pages={6869-6898},
  year={2017},
}

@article{howard2017mobilenets,
  title={Mobilenets: Efficient convolutional neural networks for mobile vision applications},
  author={Howard, Andrew G and Zhu, Menglong and Chen, Bo and Kalenichenko, Dmitry and Wang, Weijun and Weyand, Tobias and Andreetto, Marco and Adam, Hartwig},
  journal={arXiv preprint arXiv:1704.04861},
  year={2017}
}

@inproceedings{sandler2018mobilenetv2,
  title={MobileNetV2: Inverted Residuals and Linear Bottlenecks},
  author={Sandler, Mark and Howard, Andrew and Zhu, Menglong and Zhmoginov, Andrey and Chen, Liang-Chieh},
  booktitle=CVPR,
  year={2018}
}

@article{howard2019searching,
  title={Searching for MobileNetV3},
  author={Howard, Andrew and Sandler, Mark and Chu, Grace and Chen, Liang-Chieh and Chen, Bo and Tan, Mingxing and Wang, Weijun and Zhu, Yukun and Pang, Ruoming and Vasudevan, Vijay and others},
  journal={arXiv preprint arXiv:1905.02244},
  year={2019}
}

@inproceedings{zhang2017shufflenet,
  title={Shufflenet: An extremely efficient convolutional neural network for mobile devices},
  author={Zhang, Xiangyu and Zhou, Xinyu and Lin, Mengxiao and Sun, Jian},
  booktitle=CVPR,
  year=2018
}

@inproceedings{ma2018shufflenet,
  title={ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design},
  author={Ma, Ningning and Zhang, Xiangyu and Zheng, Hai-Tao and Sun, Jian},
  booktitle=ECCV,
  year={2018}
}

@inproceedings{buciluǎ2006model,
  title={Model compression},
  author={Buciluǎ, Cristian and Caruana, Rich and Niculescu-Mizil, Alexandru},
  booktitle=SIGKDD,
  year={2006},
}

@article{blumer1987occam,
  title={Occam's razor},
  author={Blumer, Anselm and Ehrenfeucht, Andrzej and Haussler, David and Warmuth, Manfred K},
  journal={Information Processing Letters},
  volume={24},
  number={6},
  pages={377--380},
  year={1987},
}

@inproceedings{li2018closed,
  title={A closed-form solution to photorealistic image stylization},
  author={Li, Yijun and Liu, Ming-Yu and Li, Xueting and Yang, Ming-Hsuan and Kautz, Jan},
  booktitle=ECCV,
  year={2018}
}

@inproceedings{jia2014caffe,
  title={Caffe: Convolutional architecture for fast feature embedding},
  author={Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
  booktitle=ACMMM,
  year={2014}
}

@inproceedings{abadi2016tensorflow,
  title={{TensorFlow}: A system for large-scale machine learning},
  author={Abadi, Mart{\'\i}n and Barham, Paul and Chen, Jianmin and Chen, Zhifeng and Davis, Andy and Dean, Jeffrey and Devin, Matthieu and Ghemawat, Sanjay and Irving, Geoffrey and Isard, Michael and others},
  booktitle=OSDI,
  year={2016}
}

@inproceedings{bastien2012theano,
  title={Theano: new features and speed improvements},
  author={Bastien, Fr{\'e}d{\'e}ric and Lamblin, Pascal and Pascanu, Razvan and Bergstra, James and Goodfellow, Ian and Bergeron, Arnaud and Bouchard, Nicolas and Warde-Farley, David and Bengio, Yoshua},
  booktitle=NIPSw,
  year={2012}
}

@inproceedings{pytorch,
  title={Automatic differentiation in PyTorch},
  author={Paszke, Adam and Gross, Sam and Chintala, Soumith and Chanan, Gregory and Yang, Edward and DeVito, Zachary and Lin, Zeming and Desmaison, Alban and Antiga, Luca and Lerer, Adam},
  booktitle=NIPSw,
  year={2017}
}

@article{chen2015mxnet,
  title={Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems},
  author={Chen, Tianqi and Li, Mu and Li, Yutian and Lin, Min and Wang, Naiyan and Wang, Minjie and Xiao, Tianjun and Xu, Bing and Zhang, Chiyuan and Zhang, Zheng},
  journal={arXiv preprint arXiv:1512.01274},
  year={2015}
}

# CNTK
@article{cntk,
  title={An introduction to computational networks and the computational network toolkit},
  author={Yu, Dong and Eversole, Adam and Seltzer, Mike and Yao, Kaisheng and Huang, Zhiheng and Guenter, Brian and Kuchaiev, Oleksii and Zhang, Yu and Seide, Frank and Wang, Huaming and others},
  journal={Microsoft Technical Report MSR-TR-2014--112},
  year={2014}
}

@article{wei2017dlvm,
  title={{DLVM}: A modern compiler infrastructure for deep learning systems},
  author={Wei, Richard and Schwartz, Lane and Adve, Vikram},
  journal={arXiv preprint arXiv:1711.03016},
  year={2017}
}

# https://www.paddlepaddle.org.cn/

@inproceedings{kingma2014adam,
  title={Adam: A method for stochastic optimization},
  author={Kingma, Diederik P and Ba, Jimmy},
  booktitle=ICLR,
  year={2015}
}

@inproceedings{zagoruyko2016paying,
  title={Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer},
  author={Zagoruyko, Sergey and Komodakis, Nikos},
  booktitle=ICLR,
  year={2017}
}

@inproceedings{chen2018darkrank,
  title={Darkrank: Accelerating deep metric learning via cross sample similarities transfer},
  author={Chen, Yuntao and Wang, Naiyan and Zhang, Zhaoxiang},
  booktitle=AAAI,
  year={2018}
}

@inproceedings{nair2010rectified,
  title={Rectified linear units improve restricted boltzmann machines},
  author={Nair, Vinod and Hinton, Geoffrey E},
  booktitle=ICML,
  year={2010}
}

@article{liu1989limited,
  title={On the limited memory BFGS method for large scale optimization},
  author={Liu, Dong C and Nocedal, Jorge},
  journal={Mathematical Programming},
  volume={45},
  number={1-3},
  pages={503--528},
  year={1989},
}


@ARTICLE{AnwSun16,
  author =       {S. Anwar and W. Sung},
  title =        {Compact Deep Convolutional Neural Networks With Coarse Pruning},
  journal =      {arXiv preprint arXiv: 1610.09639},
  year =         {2016},
}

@inproceedings{BaCar14,
  author =       {J. Ba and R. Caruana},
  title =        {Do deep nets really need to be deep?},
  booktitle =    NIPS,
  year =         {2014}
}

@inproceedings{CheWilTyrWeiChe15,
  author =       {W. Chen and J. T. Wilson and S. Tyree and K. Q. Weinberger and Y. Chen},
  title =        {Compressing neural networks with the hashing trick},
  booktitle =    ICML,
  year =         {2015},
}

# OBD
@inproceedings{CunDenSol90,
  author =       {Y. LeCun and J. S. Denker and S. A. Solla},
  title =        {Optimal brain damage},
  booktitle =    NIPS,
  year =         {1990},
}

@inproceedings{HasSto93,
  author =       {B. Hassibi and D. G. Stork},
  title =        {Second order derivatives for network pruning: Optimal brain surgeon},
  booktitle =    NIPS,
  year =         {1993},
}

@inproceedings{ChePurSim06,
  author =       {K. Chellapilla and S. Puri and P. Simard},
  title =        {High performance convolutional neural networks for document processing},
  booktitle =    {International Workshop on Frontiers in Handwriting Recognition},
  year =         {2006},
}

@ARTICLE{CheWooVan14,
  author =       {S. Chetlur and C. Woolley and P. Vandermersch},
  title =        {cu{DNN}: Efficient primitives for deep learning},
  journal =      {arXiv preprint arXiv:1410.0759},
  year =         {2014},
}

@inproceedings{DenEtAl13,
  author =       {M. Denil and B. Shakibi and L. Dinh and M. Ranzato and N. De Freitas},
  title =        {Predicting parameters in deep learning},
  booktitle =    NIPS,
  year =         {2013},
}

@MISC{Flower,
  howpublished = {\url{http://www.robots.ox.ac.uk/~vgg/data/flowers/102/index.html}},
}

@book{GooBenCou16,
  author = {I. Goodfellow and Y. Bengio and A. Courville},
  title = {Deep Learning},
  publisher={MIT Press},
  year = {2016},
}

@article{GraKriRas94,
  author = {V. Granville and M. Krivanek and J. P. Rasson},
  title = {Simulated annealing: A proof of convergence},
  journal = PAMI,
  volume = {16},
  number = {6},
  pages = {652-656},
  year = {1994},
}

@ARTICLE{HanLiuMao16,
  author =       {S. Han and X. Liu and H. Mao},
  title =        {{EIE}: efficient inference engine on compressed deep neural network},
  journal =      {{ACM} Sigarch Computer Architecture News},
  volume = {44},
  number = {3},
  pages = {243-254},
  year =         {2016},
}

@inproceedings{HeZhaRenSun16,
  author = {K. He and X. Zhang and S. Ren and J. Sun},
  title  = {Deep Residual Learning for Image Recognition},
  booktitle =   CVPR,
  year = {2016},
}

@ARTICLE{HinDenEtAl12,
  author = {G. E. Hinton and L. Deng and D. Yu and G. E. Dahl and A. R. Mohamed and N. Jaitly and A. Senior and V. Vanhoucke and P. Nguyen and T. N. Sainath and B. Kingsbury},
  title  = {Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups},
  journal = {{IEEE} Signal Processing Magazine},
  volume = {29},
  number = {6},
  pages = {82-97},
  year = {2012},
}

@ARTICLE{HinSriKri12,
  author =       {G. E. Hinton and N. Srivastava and A. Krizhevsky and I. Sutskever and R. R. Salakhutdinov},
  title =        {Improving neural networks by preventing co-adaptation of feature detectors},
  journal =      {arXiv preprint arXiv:1207.0580},
  year =         {2012},
}

@article{srivastava2014dropout,
  title={Dropout: a simple way to prevent neural networks from overfitting},
  author={Srivastava, Nitish and Hinton, Geoffrey and Krizhevsky, Alex and Sutskever, Ilya and Salakhutdinov, Ruslan},
  journal=JMLR,
  volume={15},
  number={1},
  pages={1929--1958},
  year={2014},
}

@inproceedings{glorot2010understanding,
  title={Understanding the difficulty of training deep feedforward neural networks},
  author={Glorot, Xavier and Bengio, Yoshua},
  booktitle=AISTATS,
  year={2010}
}

@inproceedings{mishkin2015all,
  title={All you need is a good init},
  author={Mishkin, Dmytro and Matas, Jiri},
  booktitle=ICLR,
  year={2016}
}

@article{krahenbuhl2015data,
  title={Data-dependent initializations of convolutional neural networks},
  author={Kr{\"a}henb{\"u}hl, Philipp and Doersch, Carl and Donahue, Jeff and Darrell, Trevor},
  journal={arXiv preprint arXiv:1511.06856},
  year={2015}
}

@inproceedings{he2015delving,
  title={Delving deep into rectifiers: Surpassing human-level performance on imagenet classification},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle=CVPR,
  year={2015}
}

@ARTICLE{IanMosAsh16,
  author =       {F. Iandola and M. Moskewicz and K. Ashraf},
  title =        {{SqueezeNet}: Alexnet-level accuracy with 50x fewer parameters and $<$0.5{MB} model size},
  journal =      {arXiv preprint arXiv:1602.07360},
  year =         {2016},
}

@ARTICLE{JiaSheDonEtAl14,
  author =       {Y. Jia and E. Shelhamer and J. Donahue and S. Karayev and J. Long and R. Girshick and S. Guadarrama and T. Darrel},
  title =        {Caffe: Convolutional architecture for fast feature embedding},
  journal =      {arXiv preprint arXiv:1408.5093},
  year =         {2014},
}

@inproceedings{KriSutHin12,
  author =       {A. Krizhevsky and I. Sutskever  and G. E. Hinton},
  title =        {Image{N}et classification with deep convolutional neural networks},
  booktitle =    NIPS,
  year =         {2012},
}

@techreport{KriHin09,
  title={Learning multiple layers of features from tiny images},
  author={Krizhevsky, Alex},
  year={2009},
  institution={Citeseer}
}

@inproceedings{Kru88,
  author = {John K. Kruschke},
  title  = {Creating local and distributed bottlenecks in hidden layers of back-propagation networks},
  booktitle = {Proc. 1988 Connectionist Models Summer School},
  year = {1988},
}


@ARTICLE{LebYarRakOseLem16,
  author =       {V. Lebedev and Y. Ganin and M. Rakhuba and  I. Oseledets and V. Lempitsky},
  title =        {Speeding-up Convolutional Neural Networks Using Fine-tuned {CP}-Decomposition},
  journal =      {arXiv preprint arXiv:1510.03009},
  year =         {2016},
}


@article{LecBenHin15,
  title={Deep learning},
  author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
  journal={Nature},
  volume={521},
  number={7553},
  pages={436},
  year={2015},
}


@MISC{Lec98,
  author =       {Y. LeCun},
  howpublished = {\url{http://yann.lecun.com/exdb/mnist/}},
  year =         {1998},
}


@article{LiuChen98,
  author = {J. S. Liu and R. Chen},
  title = {Sequential Monte Carlo methods for dynamic systems},
  journal  = {Journal of the American Statistical Association},
  volume = {93},
  number = {443},
  pages = {1032--1044},
  year = {1998},
}

@inproceedings{NilZis08,
  author = {M. E. Nilsback and A. Zisserman},
  title = {Automated flower classification over a large number of classes},
  booktitle = {Proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing},
  year = {2008},
}

@ARTICLE{NovPodOsoVet14,
  author =       {A. Novikov and D. Podoprikhin and A. Osokin and D. Vetrov},
  title =        {Tensorizing neural networks},
  journal =      {arXiv preprint arXiv:1509.06569},
  year =         {2014},
}

@inproceedings{OkuTalEtAl04,
  author = {K. Okuma and A. Taleghani and N. Freitas and J. Little and D. G. Lowe},
  title = {A boosted particle filter: Multitarget detection and tracking},
  booktitle = ECCV,
  year = {2004},
}

@inproceedings{mozer1989skeletonization,
  title={Skeletonization: A technique for trimming the fat from a network via relevance assessment},
  author={Mozer, Michael C and Smolensky, Paul},
  booktitle=NIPS,
  year={1989}
}

@ARTICLE{Ree93,
  author =       {R. Reed},
  title =        {Pruning algorithms -- a survey},
  journal =      {{IEEE} Transactions on Neural Networks},
  year =         {1993},
  volume =       {4},
  number =       {5},
  pages =        {740-747},
}

@ARTICLE{SzeCheYanEme17,
  author =       {V. Sze and Y. H. Chen and T. J. Yang and J. Emer},
  title =        {Efficient processing of deep neural networks: A tutorial and survey},
  journal =      {arXiv preprint arXiv:1703.09039},
  year =         {2017},
}

@inproceedings{SzeLiuJiaSerReeAngErhVanRab15,
  author =       {C. Szegedy and W. Liu and Y. Jia and P. Sermanet and S. Reed and D. Anguelov and D. Erhan and V. Vanhoucke and A. Rabinovich},
  title =        {Going deeper with convolutions},
  booktitle =    CVPR,
  year =         {2015},
}

@inproceedings{WuLenWanHuChe16,
  author =       {J. Wu and C. Leng and Y. Wang and Q. Hu and J. Cheng},
  title =        {Quantized Convolutional Neural Networks for Mobile Devices},
  booktitle =    CVPR,
  year =         {2016},
}

@inproceedings{Simonyan2014Very,
  title={Very Deep Convolutional Networks for Large-Scale Image Recognition},
  author={Simonyan, Karen and Zisserman, Andrew},
  booktitle=ICLR,
  year={2015}
}

@inproceedings{Chollet2016Xception,
  title={Xception: Deep Learning with Depthwise Separable Convolutions},
  author={Chollet, François},
  booktitle=CVPR,
  year={2017},
}

@inproceedings{lavin2016fast,
  title={Fast algorithms for convolutional neural networks},
  author={Lavin, Andrew and Gray, Scott},
  booktitle=CVPR,
  year={2016}
}

@inproceedings{liu2018efficient,
  title={Efficient Sparse-Winograd Convolutional Neural Networks},
  author={Liu, Xingyu and Pool, Jeff and Han, Song and Dally, William J},
  booktitle=ICLR,
  year={2018}
}

@book{winograd1980arithmetic,
  title={Arithmetic complexity of computations},
  author={Winograd, Shmuel},
  volume={33},
  year={1980},
  publisher={SIAM}
}

@book{blahut2010fast,
  title={Fast algorithms for signal processing},
  author={Blahut, Richard E},
  year={2010},
  publisher={Cambridge University Press}
}

@article{strassen1969gaussian,
  title={Gaussian elimination is not optimal},
  author={Strassen, Volker},
  journal={Numerical Mathematics},
  volume={13},
  number={4},
  pages={354--356},
  year={1969},
}

@inproceedings{cong2014minimizing,
  title={Minimizing computation in convolutional neural networks},
  author={Cong, Jason and Xiao, Bingjun},
  booktitle={International conference on artificial neural networks},
  year={2014},
}

@article{mathieu2013fast,
  title={Fast training of convolutional networks through ffts},
  author={Mathieu, Michael and Henaff, Mikael and LeCun, Yann},
  journal={arXiv preprint arXiv:1312.5851},
  year={2013}
}

@inproceedings{vasilache2014fast,
  title={Fast convolutional nets with fbfft: A GPU performance evaluation},
  author={Vasilache, Nicolas and Johnson, Jeff and Mathieu, Michael and Chintala, Soumith and Piantino, Serkan and LeCun, Yann},
  booktitle=ICLR,
  year={2015}
}

@inproceedings{molchanov2017variational,
  title={Variational dropout sparsifies deep neural networks},
  author={Molchanov, Dmitry and Ashukha, Arsenii and Vetrov, Dmitry},
  booktitle=ICML,
  year={2017}
}

@inproceedings{neklyudov2017structured,
  title={Structured bayesian pruning via log-normal multiplicative noise},
  author={Neklyudov, Kirill and Molchanov, Dmitry and Ashukha, Arsenii and Vetrov, Dmitry},
  booktitle=NIPS,
  year={2017}
}

@inproceedings{louizos2017bayesian,
  title={Bayesian compression for deep learning},
  author={Louizos, Christos and Ullrich, Karen and Welling, Max},
  booktitle=NIPS,
  year={2017}
}

@inproceedings{gal2016dropout,
  title={Dropout as a bayesian approximation: Representing model uncertainty in deep learning},
  author={Gal, Yarin and Ghahramani, Zoubin},
  booktitle=ICML,
  year={2016}
}

@inproceedings{yu2017accelerating,
  title={Accelerating convolutional neural networks by group-wise 2D-filter pruning},
  author={Yu, Niange and Qiu, Shi and Hu, Xiaolin and Li, Jianmin},
  booktitle=IJCNN,
  year={2017},
}

@inproceedings{he2018amc,
  title={{AMC}: Automl for model compression and acceleration on mobile devices},
  author={He, Yihui and Lin, Ji and Liu, Zhijian and Wang, Hanrui and Li, Li-Jia and Han, Song},
  booktitle=ECCV,
  year={2018}
}

@article{hu2018hashing,
  title={From hashing to {CNNs}: Training BinaryWeight networks via hashing},
  author={Hu, Qinghao and Wang, Peisong and Cheng, Jian},
  journal={arXiv preprint arXiv:1802.02733},
  year={2018}
}

@inproceedings{guo2016dynamic,
  title={Dynamic network surgery for efficient dnns},
  author={Guo, Yiwen and Yao, Anbang and Chen, Yurong},
  booktitle=NIPS,
  year={2016}
}

# AFP
@inproceedings{DinDinHanTan18,
  author = {Ding, Xiaohan and Ding, Guiguang and Han, Jungong and Tang, Sheng},
  title = {Auto-balanced filter pruning for efficient convolutional neural networks},
  booktitle = AAAI,
  year = {2018},
}

@article{Yuan2006Model,
  title={Model selection and estimation in regression with grouped variables},
  author={Yuan, Ming and Lin, Yi},
  journal={Journal of the Royal Statistical Society},
  volume={68},
  number={1},
  pages={49-67},
  year={2006},
}

@inproceedings{yosinski2014transferable,
  title={How transferable are features in deep neural networks?},
  author={Yosinski, Jason and Clune, Jeff and Bengio, Yoshua and Lipson, Hod},
  booktitle=NIPS,
  year={2014},
}

@article{zhong2018shift,
  title={Shift-based Primitives for Efficient Convolutional Neural Networks},
  author={Zhong, Huasong and Liu, Xianggen and He, Yihui and Ma, Yuchun and Kitani, Kris},
  journal={arXiv preprint arXiv:1809.08458},
  year={2018}
}

@inproceedings{VadLem16,
  author = {V. Lebedev and V. Lempitsky},
  title  = {Fast ConvNets Using Group-Wise Brain Damage},
  booktitle = CVPR,
  year = {2016},
}

@inproceedings{zhao2018icnet,
  author = {Zhao, Hengshuang and Qi, Xiaojuan and Shen, Xiaoyong and Shi, Jianping and Jia, Jiaya},
  title  = {{ICNet} for real-time semantic segmentation on high-resolution images},
  booktitle = ECCV,
  year = {2018},
}

@inproceedings{marchisio2018prunet,
  title={{PruNet}: Class-Blind Pruning Method for Deep Neural Networks},
  author={Marchisio, Alberto and Hanif, Muhammad Abdullah and Martina, Maurizio and Shafique, Muhammad},
  booktitle=IJCNN,
  year={2018},
}

@inproceedings{papamakarios2015distilling,
  title={Distilling intractable generative models},
  author={Papamakarios, George and Murray, Iain},
  booktitle=NIPSw,
  year={2015}
}

@inproceedings{nguyen2016multifaceted,
  title={Multifaceted feature visualization: Uncovering the different types of features learned by each neuron in deep neural networks},
  author={Nguyen, Anh and Yosinski, Jason and Clune, Jeff},
  booktitle=ICMLw,
  year={2016}
}

@inproceedings{vanhoucke2011improving,
  title={Improving the speed of neural networks on {CPUs}},
  author={Vanhoucke, Vincent and Senior, Andrew and Mao, Mark Z},
  booktitle=NIPSw,
  year={2011},
}

@inproceedings{papernot2016distillation,
  title={Distillation as a defense to adversarial perturbations against deep neural networks},
  author={Papernot, Nicolas and McDaniel, Patrick and Wu, Xi and Jha, Somesh and Swami, Ananthram},
  booktitle={IEEE Symposium on Security and Privacy},
  year={2016},
}

@inproceedings{lin2019defensive,
  title={Defensive quantization: When efficiency meets robustness},
  author={Lin, Ji and Gan, Chuang and Han, Song},
  booktitle=ICLR,
  year={2019}
}

@techreport{rumelhart1985learning,
  title={Learning internal representations by error propagation},
  author={Rumelhart, David E and Hinton, Geoffrey E and Williams, Ronald J},
  year={1985},
  institution={California Univ San Diego La Jolla Inst for Cognitive Science}
}

@inproceedings{ioffe2015batch,
  title={Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift},
  author={Ioffe, Sergey and Szegedy, Christian},
  booktitle=ICML,
  year={2015}
}

@article{pan2010survey,
  title={A survey on transfer learning},
  author={Pan, Sinno Jialin and Yang, Qiang},
  journal={IEEE Transactions on knowledge and data engineering},
  volume={22},
  number={10},
  pages={1345--1359},
  year={2010},
}

@article{Valiant1984A,
  title={A theory of the learnable},
  author={Valiant, L. G},
  journal={Communications of ACM},
  volume={27},
  number={11},
  pages={1134-1142},
  year={1984},
}

@article{Martin1999Neural,
  title={Neural Network Learning: Theoretical Foundations},
  author={Martin and Anthony},
  journal={AI Magazine},
  volume={22},
  number={2},
  pages={99-100},
  year={1999},
}

@book{Schapire2006Foundations,
  title={Foundations of Machine Learning},
  author={Schapire, Rob and Mau, Siun Chuon},
  year={2006},
  press={MIT Press}
}

@book{shalev2014understanding,
  title={Understanding machine learning: From theory to algorithms},
  author={Shalev-Shwartz, Shai and Ben-David, Shai},
  year={2014},
  press={Cambridge University Press}
}

@inproceedings{frankle2019the,
	title="The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks",
	author="Jonathan {Frankle} and Michael {Carbin}",
	booktitle=ICLR,
	year="2019"
}

@inproceedings{huang2017densely,
  title={Densely connected convolutional networks},
  author={Huang, Gao and Liu, Zhuang and Van Der Maaten, Laurens and Weinberger, Kilian Q},
  booktitle=CVPR,
  year={2017}
}

@inproceedings{bengio2007greedy,
  title={Greedy layer-wise training of deep networks},
  author={Bengio, Yoshua and Lamblin, Pascal and Popovici, Dan and Larochelle, Hugo},
  booktitle=NIPS,
  year={2007}
}

@article{ji20123d,
  title={3D convolutional neural networks for human action recognition},
  author={Ji, Shuiwang and Xu, Wei and Yang, Ming and Yu, Kai},
  journal=PAMI,
  volume={35},
  number={1},
  pages={221--231},
  year={2012},
}

@inproceedings{karpathy2014large,
  title={Large-scale video classification with convolutional neural networks},
  author={Karpathy, Andrej and Toderici, George and Shetty, Sanketh and Leung, Thomas and Sukthankar, Rahul and Fei-Fei, Li},
  booktitle=CVPR,
  year={2014}
}

@inproceedings{tran2015learning,
  title={Learning spatiotemporal features with 3d convolutional networks},
  author={Tran, Du and Bourdev, Lubomir and Fergus, Rob and Torresani, Lorenzo and Paluri, Manohar},
  booktitle=ICCV,
  year={2015}
}

@inproceedings{zhu2018knowledge,
  title={Knowledge Distillation by On-the-Fly Native Ensemble},
  author={Zhu, Xiatian and Gong, Shaogang and others},
  booktitle=NIPS,
  year={2018}
}

@inproceedings{lopes2017data,
  title={Data-free knowledge distillation for deep neural networks},
  author={Lopes, Raphael Gontijo and Fenu, Stefano and Starner, Thad},
  journal=NIPSw,
  year={2017}
}

@article{chen2019data,
  title={Data-Free Learning of Student Networks},
  author    = {Hanting Chen and
               Yunhe Wang and
               Chang Xu and
               Zhaohui Yang and
               Chuanjian Liu and
               Boxin Shi and
               Chunjing Xu and
               Chao Xu and
               Qi Tian},
  journal={arXiv preprint arXiv:1904.01186},
  year={2019}
}

@inproceedings{schroff2015facenet,
  title={Facenet: A unified embedding for face recognition and clustering},
  author={Schroff, Florian and Kalenichenko, Dmitry and Philbin, James},
  booktitle=CVPR,
  year={2015}
}

@inproceedings{radosavovic2018data,
  title={Data distillation: Towards omni-supervised learning},
  author={Radosavovic, Ilija and Doll{\'a}r, Piotr and Girshick, Ross and Gkioxari, Georgia and He, Kaiming},
  booktitle=CVPR,
  year={2018}
}

@inproceedings{lecun1990handwritten,
  title={Handwritten digit recognition with a back-propagation network},
  author={LeCun, Yann and Boser, Bernhard E and Denker, John S and Henderson, Donnie and Howard, Richard E and Hubbard, Wayne E and Jackel, Lawrence D},
  booktitle=NIPS,
  year={1990}
}

@inproceedings{zoph2017neural,
  title={Neural Architecture Search with Reinforcement Learning},
  author={Zoph, Barret and Le, Quoc},
  booktitle=ICLR,
  year={2017}
}

@article{tan2018mnasnet,
  title={Mnasnet: Platform-aware neural architecture search for mobile},
  author={Tan, Mingxing and Chen, Bo and Pang, Ruoming and Vasudevan, Vijay and Le, Quoc V},
  journal={arXiv preprint arXiv:1807.11626},
  year={2018}
}

@article{cai2019proxylessnas,
  title={ProxylessNAS: Direct neural architecture search on target task and hardware},
  author={Cai, Han and Zhu, Ligeng and Han, Song},
  booktitle=ICLR,
  year={2019}
}

@inproceedings{lu2017evaluating,
  title={Evaluating fast algorithms for convolutional neural networks on FPGAs},
  author={Lu, Liqiang and Liang, Yun and Xiao, Qingcheng and Yan, Shengen},
  booktitle={IEEE Symposium on Field-Programmable Custom Computing Machines},
  year={2017},
}

@inproceedings{yim2017gift,
  title={A gift from knowledge distillation: Fast optimization, network minimization and transfer learning},
  author={Yim, Junho and Joo, Donggyu and Bae, Jihoon and Kim, Junmo},
  booktitle=CVPR,
  year={2017}
}

@inproceedings{liu2019rethinking,
  title={Rethinking the Value of Network Pruning},
  author={Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, Trevor Darrell},
  booktitle=ICLR,
  year={2019}
}

@inproceedings{xx2018is,
  title={Pruning neural networks: is it time to nip it in the bud?},
  author={Elliot J. Crowley, Jack Turner, Amos Storkey, Michael O'Boyle},
  booktitle=NIPSw,
  year={2018}
}

# ThiNet
@inproceedings{luo2017thinet,
  title={Thinet: A filter level pruning method for deep neural network compression},
  author={Luo, Jian-Hao and Wu, Jianxin and Lin, Weiyao},
  booktitle=ICCV,
  year={2017}
}

@article{luo2018thinet,
  title={Thinet: A filter level pruning method for deep neural network compression},
  author={Luo, Jian-Hao and Wu, Jianxin and Lin, Weiyao},
  journal=PAMI,
  year={2018}
}

@article{luo2018autopruner,
  title={Autopruner: An end-to-end trainable filter pruning method for efficient deep model inference},
  author={Luo, Jian-Hao and Wu, Jianxin},
  journal={arXiv preprint arXiv:1805.08941},
  year={2018}
}

# SSS
@inproceedings{huang2018data,
  title={Data-Driven Sparse Structure Selection for Deep Neural Networks},
  author={Zehao Huang and Naiyan Wang},
  booktitle=ECCV,
  year={2018}
}

@article{shi2016edge,
  title={Edge computing: Vision and challenges},
  author={Shi, Weisong and Cao, Jie and Zhang, Quan and Li, Youhuizi and Xu, Lanyu},
  journal={IEEE Internet of Things Journal},
  volume={3},
  number={5},
  pages={637--646},
  year={2016},
}

@misc{ncnn,
  title = {{NCNN}},
  author = {Tencent},
  year = {2017},
  howpublished = {\url{https://github.com/Tencent/ncnn}},
  note = {Accessed: 2019-09-01},
}

@misc{mace,
  title = {{MACE}: Mobile AI Compute Engine},
  author = {Xiaomi},
  year = {2018},
  howpublished = {\url{https://github.com/XiaoMi/mace}},
  note = {Accessed: 2019-09-01},
}

@misc{anakin,
  title = {{Anakin}},
  author = {Baidu},
  year = {2018},
  howpublished = {\url{https://github.com/PaddlePaddle/Anakin}},
  note = {Accessed: 2019-09-01},
}

@misc{coreml,
  title = {{CoreML}},
  author = {Apple},
  year = {2017},
  howpublished = {\url{https://developer.apple.com/documentation/coreml}},
  note = {Accessed: 2019-09-01},
}

@misc{tflite,
  title = {{TensorFlow Lite}},
  author = {Google},
  year = {2017},
  howpublished = {\url{https://tensorflow.google.cn/lite}},
  note = {Accessed: 2019-09-01},
}

@misc{nnapi,
  title = {{Neural Networks API}},
  author = {Google},
  year = {2016},
  howpublished = {\url{https://developer.android.google.cn/ndk/guides/neuralnetworks}},
  note = {Accessed: 2019-09-01},
}

@misc{tvm,
  title = {{TVM}: Tensor Virtual Machine, Open Deep Learning Compiler Stack},
  author = {DMLC},
  year = {2016},
  howpublished = {\url{https://github.com/dmlc/tvm}},
  note = {Accessed: 2019-09-01},
}

@misc{xla,
  title = {{XLA}: Accelerated Linear Algebra},
  author = {Google},
  year = {2017},
  howpublished = {\url{https://developers.googleblog.com/2017/03/xla-tensorflow-compiled.html}},
  note = {Accessed: 2019-09-01},
}

@misc{biglittle,
  title = {{ARM big.LITTLE}: Processing architecture for power efficiency and performance},
  author = {ARM},
  year = {2011},
  howpublished = {\url{https://www.arm.com/why-arm/technologies/big-little}},
  note = {Accessed: 2019-09-01},
}

@misc{metal,
  title = {{Metal: Accelerating graphics and much more}},
  author = {Apple},
  year = {2014},
  howpublished = {\url{https://developer.apple.com/metal/}},
  note = {Accessed: 2019-09-01},
}

@misc{opencl,
  title = {{OpenCL: Open Computing Language}},
  author = {Khronos, Group},
  year = {2009},
  howpublished = {\url{https://www.khronos.org/opencl/}},
  note = {Accessed: 2019-09-01},
}

@misc{opengl,
  title = {{OpenGL: Open Graphics Library}},
  author = {Khronos, Group},
  year = {1992},
  howpublished = {\url{https://opengl.org/}},
  note = {Accessed: 2019-09-01},
}

@misc{vulkan,
  title = {{Vulkan}},
  author = {Khronos, Group},
  year = {2015},
  howpublished = {\url{https://www.khronos.org/vulkan}},
  note = {Accessed: 2019-09-01},
}

@misc{tfwinograd,
  title = {{TensorFlow Winograd}},
  author = {Google},
  howpublished = {\url{https://github.com/tensorflow/tensorflow/blob/9590c4c32dd4346ea5c35673336f5912c6072bf2/tensorflow/core/kernels/winograd\_transform.h}},
  note = {Accessed: 2019-09-01},
}

@misc{macewinograd,
  title = {{MACE Winograd}},
  author = {Xiaomi},
  howpublished = {\url{https://github.com/XiaoMi/mace/blob/9b0b03c99cf73cd019050c6b9ee80a4753265da0/mace/ops/arm/fp32/conv_2d_3x3_winograd.cc}},
  note = {Accessed: 2019-09-01},
}



@inproceedings{liu2016ssd,
  title={{SSD}: Single shot multibox detector},
  author={Liu, Wei and Anguelov, Dragomir and Erhan, Dumitru and Szegedy, Christian and Reed, Scott and Fu, Cheng-Yang and Berg, Alexander C},
  booktitle=ECCV,
  year={2016},
}

# ATLAS
@inproceedings{whaley1998automatically,
  title={Automatically tuned linear algebra software},
  author={Whaley, R Clinton and Dongarra, Jack J},
  booktitle={Proceedings of the ACM/IEEE conference on Supercomputing},
  year={1998},
}

@inproceedings{frigo1998fftw,
  title={{FFTW}: An adaptive software architecture for the FFT},
  author={Frigo, Matteo and Johnson, Steven G},
  booktitle=ICASSP,
  year={1998},
}

@article{vasilache2018tensor,
  title={Tensor comprehensions: Framework-agnostic high-performance machine learning abstractions},
  author={Vasilache, Nicolas and Zinenko, Oleksandr and Theodoridis, Theodoros and Goyal, Priya and DeVito, Zachary and Moses, William S and Verdoolaege, Sven and Adams, Andrew and Cohen, Albert},
  journal={arXiv preprint arXiv:1802.04730},
  year={2018}
}

@inproceedings{truong2016latte,
  title={Latte: a language, compiler, and runtime for elegant and efficient deep neural networks},
  author={Truong, Leonard and Barik, Rajkishore and Totoni, Ehsan and Liu, Hai and Markley, Chick and Fox, Armando and Shpeisman, Tatiana},
  booktitle={ACM SIGPLAN Notices},
  year={2016},
}

@inproceedings{ragan2013halide,
  title={Halide: a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines},
  author={Ragan-Kelley, Jonathan and Barnes, Connelly and Adams, Andrew and Paris, Sylvain and Durand, Fr{\'e}do and Amarasinghe, Saman},
  booktitle={Acm Sigplan Notices},
  year={2013},
}

@inproceedings{lattner2004llvm,
  title={{LLVM}: A compilation framework for lifelong program analysis \& transformation},
  author={Lattner, Chris and Adve, Vikram},
  booktitle={Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization},
  year={2004},
}

@inproceedings{zeiler2014visualizing,
  title={Visualizing and understanding convolutional networks},
  author={Zeiler, Matthew D and Fergus, Rob},
  booktitle=ECCV,
  year={2014},
}

# BLAS
@article{lawson1979basic,
  title={Basic Linear Algebra Subprograms for Fortran Usage},
  author={LAWSON, CL and HANSON, RJ and KINCAID, DR and KROGH, FT},
  journal={ACM Transactions on Mathematical Software},
  volume={5},
  number={3},
  pages={308--323},
  year={1979}
}

@article{dongarra1990algorithm,
  title={Algorithm 679: A set of level 3 basic linear algebra subprograms: model implementation and test programs},
  author={Dongarra, Jack J and Cruz, Jermey Du and Hammarling, Sven and Duff, Iain S},
  journal={ACM Transactions on Mathematical Software (TOMS)},
  volume={16},
  number={1},
  pages={18--28},
  year={1990},
}

@inproceedings{anderson1990lapack,
  title={{LAPACK}: A portable linear algebra library for high-performance computers},
  author={Anderson, Edward and Bai, Zhaojun and Dongarra, Jack and Greenbaum, Anne and McKenney, Alan and Du Croz, Jeremy and Hammarling, Sven and Demmel, James and Bischof, C and Sorensen, Danny},
  booktitle={Proceedings of the ACM/IEEE conference on Supercomputing},
  year={1990},
}

@book{kennedy2001optimizing,
  title={Optimizing compilers for modern architectures: a dependence-based approach},
  author={Kennedy, Ken and Allen, John R},
  year={2001},
  publisher={Morgan Kaufmann}
}

@inproceedings{ashari2015optimizing,
  title={On optimizing machine learning workloads via kernel fusion},
  author={Ashari, Arash and Tatikonda, Shirish and Boehm, Matthias and Reinwald, Berthold and Campbell, Keith and Keenleyside, John and Sadayappan, P},
  booktitle={ACM SIGPLAN Notices},
  year={2015},
}

@inproceedings{jiang2018efficient,
  title={Efficient Deep Learning Inference on Edge Devices},
  author={Jiang, Ziheng and Chen, Tianqi and Li, Mu},
  booktitle=SYSML,
  year={2018}
}

# ------------------------
# last update: 2019-08-02
# ------------------------